DengYiping opened a new pull request, #18447:
URL: https://github.com/apache/iceberg/pull/18447

   When a Parquet Variant group contains metadata but omits its payload, the 
vectorized reader returns SQL NULL while the row reader returns Variant null 
(`00`). Use required metadata to determine presence and null counts, and 
normalize missing payloads to `00`, following the [Parquet 
specification](https://github.com/apache/parquet-format/blob/master/VariantShredding.md#value-shredding).
 This fixes Spark 4.0, 4.1, and 4.2 while preserving ordinary SQL NULL.
   
   Test plan:
   - Reproduced four failures using actual Parquet files before fixing.
   - Cover missing payloads, explicit Variant null, and SQL NULL with 
required/optional groups and dictionary encoding enabled/disabled; verify 
payload bytes and null counts.
   - All 24 focused tests pass across the three Spark versions, including 
existing Variant projection tests. Java formatting and main/test Checkstyle 
checks pass.
   
   ---
   **AI Disclosure**
   - Model: GPT-6
   - Platform/Tool: Codex
   - Human Oversight: human reproduced the problem & review the changes
   - Prompt Summary: Reproduce and surgically fix missing Variant payload 
handling. The vector changes and regression tests were generated by Codex.


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